The EMBL Nucleotide Sequence Database

Molecular basis of hyper-thermostability in the thermophilic archaeal aldolase MfnB

Methanogenic archaea are chemolithotrophic prokaryotes that can reduce carbon dioxide with hydrogen gas to form methane. These microorganisms make a significant contribution to the global carbon cycle, with methanogenic archaea from anoxic environments estimated to contribute > 500 million tons of global methane annually. Archaeal methanogenesis is dependent on the methanofurans; aminomethylfuran containing coenzymes that act as the primary C1 acceptor molecule during carbon dioxide fixation. Although the biosynthetic pathway to the methanofurans has been elucidated, structural adaptations which confer thermotolerance to Mfn enzymes from extremophilic archaea are yet to be investigated. Here we focus on the methanofuran biosynthetic enzyme MfnB, which catalyses the condensation of two molecules of glyceralde-3-phosphate to form 4‑(hydroxymethyl)-2-furancarboxaldehyde-phosphate. In this study, MfnB enzymes from the hyperthermophile Methanocaldococcus jannaschii and the mesophile Methanococcus maripaludis have been recombinantly overexpressed and purified to homogeneity. Thermal unfolding studies, together with steady-state kinetic assays, demonstrate thermoadaptation in the M. jannaschii enzyme. Molecular dynamics simulations have been used to provide a structural explanation for the observed properties. These reveal a greater number of side chain interactions in the M. jannaschii enzyme, which may confer protection from heating effects by enforcing spatial residue constraints.

Advanced piperazine-containing inhibitors target microbial β-glucuronidases linked to gut toxicity

The gut microbiome plays critical roles in human homeostasis, disease progression, and pharmacological efficacy through diverse metabolic pathways. Gut bacterial β-glucuronidase (GUS) enzymes reverse host phase 2 metabolism, in turn releasing active hormones and drugs that can be reabsorbed into systemic circulation to affect homeostasis and promote toxic side effects. The FMN-binding and loop 1 gut microbial GUS proteins have been shown to drive drug and toxin reactivation. Here we report the structure-activity relationships of two selective piperazine-containing bacterial GUS inhibitors. We explore the potency and mechanism of action of novel compounds using purified GUS enzymes and co-crystal structures. Our results establish the importance of the piperazine nitrogen placement and nucleophilicity as well as the presence of a cyclohexyl moiety appended to the aromatic core. Using these insights, we synthesized an improved microbial GUS inhibitor, UNC10206581, that potently inhibits both the FMN-binding and loop 1 GUS enzymes in the human gut microbiome, does not inhibit bovine GUS, and is non-toxic within a relevant dosing range. Kinetic analyses demonstrate that UNC10206581 undergoes a slow-binding and substrate-dependent mechanism of inhibition similar to that of the parent scaffolds. Finally, we show that UNC10206581 displays potent activity within the physiologically relevant systems of microbial cultures and human fecal protein lysates examined by metagenomic and metaproteomic methods. Together, these results highlight the discovery of more effective bacterial GUS inhibitors for the alleviation of microbe-mediated homeostatic dysregulation and drug toxicities and potential therapeutic development.

The evolution of computational research in a data-centric world

Computational data-centric research techniques play a prevalent and multi-disciplinary role in life science research. In the past, scientists in wet labs generated the data, and computational researchers focused on creating tools for the analysis of those data. Computational researchers are now becoming more independent and taking leadership roles within biomedical projects, leveraging the increased availability of public data. We are now able to generate vast amounts of data, and the challenge has shifted from data generation to data analysis. Here we discuss the pitfalls, challenges, and opportunities facing the field of data-centric research in biology. We discuss the evolving perception of computational data-driven research and its rise as an independent domain in biomedical research while also addressing the significant collaborative opportunities that arise from integrating computational research with experimental and translational biology. Additionally, we discuss the future of data-centric research and its applications across various areas of the biomedical field.

Transcription factor CmHSFA4-CmMYBS3 complex enhances salt tolerance in chrysanthemum by repressing CmMYB121 expression

Excessive soil salinity not only hampers plant growth and development but can also lead to plant death. Previously, we found that heat-shock factor A4 (CmHSFA4) enhances the tolerance of chrysanthemum (Chrysanthemum morifolium) to salt. However, the underlying molecular mechanism remains unclear. In this study, we identified a candidate MYB transcription factor, CmMYB121, which responded to salt stress. We observed that the CmMYB121 transcription is suppressed by CmHSFA4. Moreover, overexpression of CmMYB121 exacerbated chrysanthemum sensitivity to salt stress. CmHSFA4 directly bound to the promoter of CmMYB121 at the heat-shock element. Protein-protein interaction assays identified an interaction between CmHSFA4 and CmMYBS3, a transcriptional repressor, and recruited the corepressor TOPLESS (CmTPL) to inhibit CmMYB121 transcription by impairing the H3 and H4 histone acetylation levels of CmMYB121. Our study demonstrated that a CmHSFA4-CmMYBS3-CmTPL complex modulates CmMYB121 expression, consequently regulating the tolerance of chrysanthemum to salt. The findings shed light on the responses of plants to salt stress.

Transcriptome analysis: a powerful tool to understand individual microbial behaviors and interactions in ecosystems

Transcriptome analysis is a powerful tool for studying microbial ecology, especially individual microbial functions in an ecosystem and their interactions. With the development of high-throughput sequencing technology, great progress has been made in analytical methods for microbial communities in natural environments. 16S rRNA gene amplicon sequencing (ie microbial community structure analysis) and shotgun metagenome analysis have been widely used to determine the composition and potential metabolic capability of microorganisms in target environments without requiring culture. However, even if the types of microorganisms present and their genes are known, it is difficult to determine what they are doing in an ecosystem. Gene expression analysis (transcriptome analysis; RNA-seq) is a powerful tool to address these issues. The history and basic information of gene expression analysis, as well as examples of studies using this method to analyze microbial ecosystems, are presented.

Trypanosoma cruzi Vps34 colocalizes with Beclin1 and plays a role in parasite invasion of the host cell by modulating the expression of a sub-group of trans-sialidases

Trypanosoma cruzi, the etiological agent of Chagas' disease, can infect both phagocytic and non-phagocytic cells. T. cruzi gp82 and gp90 are cell surface proteins belonging to Group II trans-sialidases known to be involved in host cell binding and invasion. Phosphatidylinositol kinases (PIK) are lipid kinases that phosphorylate phospholipids in their substrates or in themselves, regulating important cellular functions such as metabolism, cell cycle and survival. Vps34, a class III PIK, regulates autophagy, trimeric G-protein signaling, and the mTOR (mammalian Target of Rapamycin) nutrient-sensing pathway. The mammalian autophagy gene Beclin1 interacts to Vps34 forming Beclin 1-Vps34 complexes involved in autophagy and protein sorting. In T. cruzi epimastigotes, (a non-infective replicative form), TcVps34 has been related to morphological and functional changes associated to vesicular trafficking, osmoregulation and receptor-mediated endocytosis. We aimed to characterize the role of TcVps34 during invasion of HeLa cells by metacyclic (MT) forms. MTs overexpressing TcVps34 showed lower invasion rates compared to controls, whilst exhibiting a significant decrease in gp82 expression in the parasite surface. In addition, we showed that T. cruzi Beclin (TcBeclin1) colocalizes with TcVps34 in epimastigotes, thus suggesting the formation of complexes that may play conserved cellular roles already described for other eukaryotes.

Gut microbial β-glucuronidases influence endobiotic homeostasis and are modulated by diverse therapeutics

Hormones and neurotransmitters are essential to homeostasis, and their disruptions are connected to diseases ranging from cancer to anxiety. The differential reactivation of endobiotic glucuronides by gut microbial β-glucuronidase (GUS) enzymes may influence interindividual differences in the onset and treatment of disease. Using multi-omic, in vitro, and in vivo approaches, we show that germ-free mice have reduced levels of active endobiotics and that distinct gut microbial Loop 1 and FMN GUS enzymes drive hormone and neurotransmitter reactivation. We demonstrate that a range of FDA-approved drugs prevent this reactivation by intercepting the catalytic cycle of the enzymes in a conserved fashion. Finally, we find that inhibiting GUS in conventional mice reduces free serotonin and increases its inactive glucuronide in the serum and intestines. Our results illuminate the indispensability of gut microbial enzymes in sustaining endobiotic homeostasis and indicate that therapeutic disruptions of this metabolism promote interindividual response variabilities.

Redesigning the Drosophila histone gene cluster: An improved genetic platform for spatiotemporal manipulation of histone function

Mutating replication-dependent (RD) histone genes is an important tool for understanding chromatin-based epigenetic regulation. Deploying this tool in metazoan models is particularly challenging because RD histones in these organisms are typically encoded by many genes, often located at multiple loci. Such RD histone gene arrangements make the ability to generate homogenous histone mutant genotypes by site-specific gene editing quite difficult. Drosophila melanogaster provides a solution to this problem because the RD histone genes are organized into a single large tandem array that can be deleted and replaced with transgenes containing mutant histone genes. In the last ∼15 years several different RD histone gene replacement platforms have been developed using this simple strategy. However, each platform contains weaknesses that preclude full use of the powerful developmental genetic capabilities available to Drosophila researchers. Here we describe the development of a newly engineered platform that rectifies many of these weaknesses. We used CRISPR to precisely delete the RD histone gene array ( HisC ), replacing it with a multifunctional cassette that permits site-specific insertion of either one or two synthetic gene arrays using selectable markers. We designed this cassette with the ability to selectively delete each of the integrated gene arrays in specific tissues using site-specific recombinases. We also present a method for rapidly synthesizing histone gene arrays of any genotype using Golden Gate cloning technologies. These improvements facilitate generation of histone mutant cells in various tissues at different stages of Drosophila development and provide an opportunity to apply forward genetic strategies to interrogate chromatin structure and gene regulation.

Redefining the treponemal history through pre-Columbian genomes from Brazil

The origins of treponemal diseases have long remained unknown, especially considering the sudden onset of the first syphilis epidemic in the late 15th century in Europe and its hypothesized arrival from the Americas with Columbus' expeditions1,2. Recently, ancient DNA evidence has revealed various treponemal infections circulating in early modern Europe and colonial-era Mexico3-6. However, there has been to our knowledge no genomic evidence of treponematosis recovered from either the Americas or the Old World that can be reliably dated to the time before the first trans-Atlantic contacts. Here, we present treponemal genomes from nearly 2,000-year-old human remains from Brazil. We reconstruct four ancient genomes of a prehistoric treponemal pathogen, most closely related to the bejel-causing agent Treponema pallidum endemicum. Contradicting the modern day geographical niche of bejel in the arid regions of the world, the results call into question the previous palaeopathological characterization of treponeme subspecies and showcase their adaptive potential. A high-coverage genome is used to improve molecular clock date estimations, placing the divergence of modern T. pallidum subspecies firmly in pre-Columbian times. Overall, our study demonstrates the opportunities within archaeogenetics to uncover key events in pathogen evolution and emergence, paving the way to new hypotheses on the origin and spread of treponematoses.

MicroAnnot: A Dedicated Workflow for Accurate Microsporidian Genome Annotation

With nearly 1700 species, Microsporidia represent a group of obligate intracellular eukaryotes with veterinary, economic and medical impacts. To help understand the biological functions of these microorganisms, complete genome sequencing is routinely used. Nevertheless, the proper prediction of their gene catalogue is challenging due to their taxon-specific evolutionary features. As innovative genome annotation strategies are needed to obtain a representative snapshot of the overall lifestyle of these parasites, the MicroAnnot tool, a dedicated workflow for microsporidian sequence annotation using data from curated databases of accurately annotated microsporidian genes, has been developed. Furthermore, specific modules have been implemented to perform small gene (<300 bp) and transposable element identification. Finally, functional annotation was performed using the signature-based InterProScan software. MicroAnnot's accuracy has been verified by the re-annotation of four microsporidian genomes for which structural annotation had previously been validated. With its comparative approach and transcriptional signal identification method, MicroAnnot provides an accurate prediction of translation initiation sites, an efficient identification of transposable elements, as well as high specificity and sensitivity for microsporidian genes, including those under 300 bp.

scTEA-db: a comprehensive database of novel terminal exon isoforms identified from human single cell transcriptomes

The usage of alternative terminal exons results in messenger RNA (mRNA) isoforms that differ in their 3' untranslated regions (3' UTRs) and often also in their protein-coding sequences. Alternative 3' UTRs contain different sets of cis-regulatory elements known to regulate mRNA stability, translation and localization, all of which are vital to cell identity and function. In previous work, we revealed that ∼25 percent of the experimentally observed RNA 3' ends are located within regions currently annotated as intronic, indicating that many 3' end isoforms remain to be uncovered. Also, the inclusion of not yet annotated terminal exons is more tissue specific compared to the already annotated ones. Here, we present the single cell-based Terminal Exon Annotation database (scTEA-db, www.scTEA-db.org) that provides the community with 12 063 so far not yet annotated terminal exons and associated transcript isoforms identified by analysing 53 069 publicly available single cell transcriptomes. Our scTEA-db web portal offers an array of features to find and explore novel terminal exons belonging to 5538 human genes, 110 of which are known cancer drivers. In summary, scTEA-db provides the foundation for studying the biological role of large numbers of so far not annotated terminal exon isoforms in cell identity and function.

PhageScope: a well-annotated bacteriophage database with automatic analyses and visualizations

Bacteriophages are viruses that infect bacteria or archaea. Understanding the diverse and intricate genomic architectures of phages is essential to study microbial ecosystems and develop phage therapy strategies. However, the existing phage databases are short of meticulous annotations. To this end, we propose PhageScope (https://phagescope.deepomics.org), an online phage database with comprehensive annotations. PhageScope harbors a collection of 873 718 phage sequences from various sources. Applying fifteen state-of-the-art tools to perform systematic annotations and analyses, PhageScope provides annotations on genome completeness, host range, lifestyle information, taxonomy classification, nine types of structural and functional genetic elements, and three types of comparative genomic studies for curated phages. Additionally, PhageScope incorporates automatic analyses and visualizations for curated and customized phages, serving as an efficient platform for phage study.

Optimizing detectability of the endangered fan mussel using eDNA and ddPCR

Spatial and temporal monitoring of species threatened with extinction is of critical importance for conservation and ecosystem management. In the Mediterranean coast, the fan mussel (Pinna nobilis) is listed as critically endangered after suffering from a mass mortality event since 2016, leading to 100% mortality in most marine populations. Conventional monitoring for this macroinvertebrate is done using scuba, which is challenging in dense meadows or with low visibility. Here we developed an environmental DNA assay targeting the fan mussel and assessed the influence of several environmental parameters on the species detectability in situ. We developed and tested an eDNA molecular marker and collected 48 water samples in two sites at the Thau lagoon (France) with distinct fan mussel density, depths and during two seasons (summer and autumn). Our marker can amplify fan mussel DNA but lacks specificity since it also amplifies a conspecific species (Pinna rudis). We successfully amplified fan mussel DNA from in situ samples with 46 positive samples (out of 48) using ddPCR, although the DNA concentrations measured were low over almost all samples. Deeper sampling depth slightly increased DNA concentrations, but no seasonal effect was found. We highlight a putative spawning event on a single summer day with much higher DNA concentration compared to all other samples. We present an eDNA molecular assay able to detect the endangered fan mussel and provide guidelines to optimize the sampling protocol to maximize detectability. Effective and non-invasive monitoring tools for endangered species are promising to monitor remaining populations and have the potential of ecological restoration or habitat recolonization following a mass mortality event.

Computational Insights into the Selecting Mechanism of α-Amylase Immobilized on Cellulose Nanocrystals: Unveiling the Potential of α-Amylases Immobilized for Efficient Poultry Feed Hydrolysis

The selection of an appropriate amylase for hydrolysis poultry feed is crucial for achieving improved digestibility and high-quality feed. Cellulose nanocrystals (CNCs), which are known for their high surface area, provide an excellent platform for enzyme immobilization. Immobilization greatly enhances the operational stability of α-amylases and the efficiency of starch bioconversion in poultry feeds. In this study, we immobilized two metagenome-derived α-amylases, PersiAmy2 and PersiAmy3, on CNCs and employed computational methods to characterize and compare the degradation efficiencies of these enzymes for poultry feed hydrolysis. Experimental in vitro bioconversion assessments were performed to validate the computational outcomes. Molecular docking studies revealed the superior hydrolysis performance of PersiAmy3, which displayed stronger electrostatic interactions with CNCs. Experimental characterization demonstrated the improved performance of both α-amylases after immobilization at high temperatures (80 °C). A similar trend was observed under alkaline conditions, with α-amylase activity reaching 88% within a pH range of 8.0 to 9.0. Both immobilized α-amylases exhibited halotolerance at NaCl concentrations up to 3 M and retained over 50% of their initial activity after 13 use cycles. Notably, PersiAmy3 displayed more remarkable improvements than PersiAmy2 following immobilization, including a significant increase in activity from 65 to 80.73% at 80 °C, an increase in activity to 156.48% at a high salinity of 3 M NaCl, and a longer half-life, indicating greater thermal stability within the range of 60 to 80 °C. These findings were substantiated by the in vitro hydrolysis of poultry feed, where PersiAmy3 generated 53.53 g/L reducing sugars. This comprehensive comparison underscores the utility of computational methods as a faster and more efficient approach for selecting optimal enzymes for poultry feed hydrolysis, thereby providing valuable insights into enhancing feed digestibility and quality.

Structure of plant-associated microeukaryotes in roots and leaves of aquatic and terrestrial plants revealed by blocking peptide-nucleic acid (PNA) amplification

Studies of plant-microbe interactions, including mutualistic, antagonistic, parasitic, or commensal microbes, have greatly benefited our understanding of ecosystem functioning. New molecular identification tools have increasingly revealed the association patterns between microorganisms and plants. Here, we integrated long-read PacBio single-molecule sequencing technology with a blocking protein-nucleic acid (PNA) approach to minimise plant amplicons in a survey of plant-eukaryotic microbe relationships in roots and leaves of different aquatic and terrestrial plants to determine patterns of organ, host, and habitat preferences. The PNA approach reduced the samples' relative amounts of plant reads and did not distort the fungal and other microeukaryotic composition. Our analyses revealed that the eukaryotic microbiomes associated with leaves and roots of aquatic plants exhibit a much larger proportion of non-fungal microorganisms than terrestrial plants, and leaf and root microbiomes are similar. Terrestrial plants had much stronger differentiation of leaf and root microbiomes and stronger partner specificity than aquatic plants.

Multiomic prediction of therapeutic targets for human diseases associated with protein phase separation

The phenomenon of protein phase separation (PPS) underlies a wide range of cellular functions. Correspondingly, the dysregulation of the PPS process has been associated with numerous human diseases. To enable therapeutic interventions based on the regulation of this association, possible targets should be identified. For this purpose, we present an approach that combines the multiomic PandaOmics platform with the FuzDrop method to identify PPS-prone disease-associated proteins. Using this approach, we prioritize candidates with high PandaOmics and FuzDrop scores using a profiling method that accounts for a wide range of parameters relevant for disease mechanism and pharmacological intervention. We validate the differential phase separation behaviors of three predicted Alzheimer's disease targets (MARCKS, CAMKK2, and p62) in two cell models of this disease. Overall, the approach that we present generates a list of possible therapeutic targets for human diseases associated with the dysregulation of the PPS process.

Chromosome-level genome of butterflyfish unveils genomic features of unique colour patterns and morphological traits

Chaetodontidae, known as butterflyfishes, are typical fish in coral ecosystems, exhibiting remarkable interspecific differences including body colour patterns and feeding ecology. In this study, we report genomes of three butterflyfish species (Chelmon rostratus, Chaetodon trifasciatus and Chaetodon auriga) and a closely related species from the Pomacanthidae family, Centropyge bicolour, with an average genome size of 65,611 Mb. Chelmon rostratus, comprising 24 chromosomes assembled to the chromosome level, could be served as a reference genome for butterflyfish. By conducting a collinearity analysis between butterflyfishes and several fishes, we elucidated the specific and conserved genomic features of butterflyfish, with particular emphasis on novel genes arising from tandem duplications and their potential functions. In addition to the two melanocyte-specific tyr genes commonly found in fish, we found the gene tyrp3, a new tyrosinase-related proteins gene in the reef fish, including butterflyfish and clownfish, implicating their involvement in the pigmentation diversity of fish. Additionally, we observed a tandem duplication expansion of three copies of nell1 gene in C. rostratus genome, which likely contribute to its unique jaw development and distinctive morphology of its sharp mouth. These results provided valuable genomic resources for further investigations into the genetic diversity and evolutionary adaptations of reef fish.

Global Antimicrobial Resistance Gene Study of Helicobacter pylori: Comparison of Detection Tools, ARG and Efflux Pump Gene Analysis, Worldwide Epidemiological Distribution, and Information Related to the Antimicrobial-Resistant Phenotype

We conducted a global-scale study to identify H. pylori antimicrobial-resistant genes (ARG), address their global distribution, and understand their effect on the antimicrobial resistance (AMR) phenotypes of the clinical isolates. We identified ARG using several well-known tools against extensive bacterial ARG databases, then analyzed their correlation with clinical antibiogram data from dozens of patients across countries. This revealed that combining multiple tools and databases, followed by manual selection of ARG from the annotation results, produces more conclusive results than using a single tool or database alone. After curation, the results showed that H. pylori has 42 ARG against 11 different antibiotic classes (16 genes related to single antibiotic class resistance and 26 genes related to multidrug resistance). Further analysis revealed that H. pylori naturally harbors ARG in the core genome, called the 'Set of ARG commonly found in the Core Genome of H. pylori (ARG-CORE)', while ARG-ACC-the ARG in the accessory genome-are exclusive to particular strains. In addition, we detected 29 genes of potential efflux pump-related AMR that were mostly categorized as ARG-CORE. The ARG distribution appears to be almost similar either by geographical or H. pylori populations perspective; however, some ARG had a unique distribution since they tend to be found only in a particular region or population. Finally, we demonstrated that the presence of ARG may not directly correlate with the sensitive/resistance phenotype of clinical patient isolates but may influence the minimum inhibitory concentration phenotype.

Complete mitochondrial genome of the Galápagos sea lion, Zalophuswollebaeki (Carnivora, Otariidae): paratype specimen confirms separate species status

The endangered Galápagos sea lion (Zalophuswollebaeki) inhabits the Galápagos Islands off the coast of Ecuador. We present a complete mitochondrial genome (16 465 bp) of a female paratype from the collections of the Natural History Museum Oslo, Norway, assembled from next-generation sequencing reads. It contains all canonical protein-coding, rRNA, tRNA genes, and the D-loop region. Sequence similarity is 99.93% to a previously published conspecific mitogenome sequence and 99.37% to the mitogenome sequence of the sister species Z.californianus. Sequence similarity of the D-loop region of the Z.wollebaeki paratype mitogenome is >99%, while the sequence difference to the Z.californianus sequences exceeds 2.5%. The paratype mitogenome sequence supports the taxonomic status of Z.wollebaeki as a separate species.

Microbial β-glucuronidases drive human periodontal disease etiology

Periodontitis is a chronic inflammatory disease associated with persistent oral microbial dysbiosis. The human β-glucuronidase (GUS) degrades constituents of the periodontium and is used as a biomarker for periodontitis severity. However, the human microbiome also encodes GUS enzymes, and the role of these factors in periodontal disease is poorly understood. Here, we define the 53 unique GUSs in the human oral microbiome and examine diverse GUS orthologs from periodontitis-associated pathogens. Oral bacterial GUS enzymes are more efficient polysaccharide degraders and processers of biomarker substrates than the human enzyme, particularly at pHs associated with disease progression. Using a microbial GUS-selective inhibitor, we show that GUS activity is reduced in clinical samples obtained from individuals with untreated periodontitis and that the degree of inhibition correlates with disease severity. Together, these results establish oral GUS activity as a biomarker that captures both host and microbial contributions to periodontitis, facilitating more efficient clinical monitoring and treatment paradigms for this common inflammatory disease.

Peptidomics

Peptides are biopolymers, typically consisting of 2-50 amino acids. They are biologically produced by the cellular ribosomal machinery or by non-ribosomal enzymes and, sometimes, other dedicated ligases. Peptides are arranged as linear chains or cycles, and include post-translational modifications, unusual amino acids and stabilizing motifs. Their structure and molecular size render them a unique chemical space, between small molecules and larger proteins. Peptides have important physiological functions as intrinsic signalling molecules, such as neuropeptides and peptide hormones, for cellular or interspecies communication, as toxins to catch prey or as defence molecules to fend off enemies and microorganisms. Clinically, they are gaining popularity as biomarkers or innovative therapeutics; to date there are more than 60 peptide drugs approved and more than 150 in clinical development. The emerging field of peptidomics comprises the comprehensive qualitative and quantitative analysis of the suite of peptides in a biological sample (endogenously produced, or exogenously administered as drugs). Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and innovative computational biology, with a specialized set of tools. The complex biological matrices and often low abundance of analytes typically examined in peptidomics experiments require optimized sample preparation and isolation, including in silico analysis. This Primer covers the combination of techniques and workflows needed for peptide discovery and characterization and provides an overview of various biological and clinical applications of peptidomics.

The global depth range of marine fishes and their genetic coverage for environmental DNA metabarcoding

The bathymetric and geographical distribution of marine species represent a key information in biodiversity conservation. Yet, deep-sea ecosystems are among the least explored on Earth and are increasingly impacted by human activities. Environmental DNA (eDNA) metabarcoding has emerged as a promising method to study fish biodiversity but applications to the deep-sea are still scarce. A major limitation in the application of eDNA metabarcoding is the incompleteness of species sequences available in public genetic databases which reduces the extent of detected species. This incompleteness by depth is still unknown. Here, we built the global bathymetric and geographical distribution of 10,826 actinopterygian and 960 chondrichthyan fish species. We assessed their genetic coverage by depth and by ocean for three main metabarcoding markers used in the literature: teleo and MiFish-U/E. We also estimated the number of primer mismatches per species amplified by in silico polymerase chain reaction which influence the probability of species detection. Actinopterygians show a stronger decrease in species richness with depth than Chondrichthyans. These richness gradients are accompanied by a continuous species turnover between depths. Fish species coverage with the MiFish-U/E markers is higher than with teleo while threatened species are more sequenced than the others. "Deep-endemic" species, those not ascending to the shallow depth layer, are less sequenced than not threatened species. The number of primer mismatches is not higher for deep-sea species than for shallower ones. eDNA metabarcoding is promising for species detection in the deep-sea to better account for the 3-dimensional structure of the ocean in marine biodiversity monitoring and conservation. However, we argue that sequencing efforts on "deep-endemic" species are needed.

Diverse but desolate landscape of gut microbial azoreductases: A rationale for idiopathic IBD drug response

Prodrugs reliant on microbial activation are widely used but exhibit a range of efficacies that remain poorly understood. The anti-inflammatory compound 5-aminosalicylic acid (5-ASA), which is packaged in a variety of azo-linked prodrugs provided to most Ulcerative Colitis (UC) patients, shows confounding inter-individual variabilities in response. Such prodrugs must be activated by azo-bond reduction to form 5-ASA, a process that has been attributed to both enzymatic and non-enzymatic catalysis. Gut microbial azoreductases (AzoRs) are the first catalysts shown to activate azo-linked drugs and to metabolize toxic azo-chemicals. Here, we chart the scope of the structural and functional diversity of AzoRs in health and in patients with the inflammatory bowel diseases (IBDs) UC and Crohn's Disease (CD). Using structural metagenomics, we define the landscape of gut microbial AzoRs in 413 healthy donor and 1059 IBD patient fecal samples. Firmicutes encode a significantly higher number of unique AzoRs compared to other phyla. However, structural and biochemical analyses of distinct AzoRs from the human microbiome reveal significant differences between prevalent orthologs in the processing of toxic azo-dyes, and their generally poor activation of IBD prodrugs. Furthermore, while individuals with IBD show higher abundances of AzoR-encoding gut microbial taxa than healthy controls, the overall abundance of AzoR-encoding microbes is markedly low in both disease and health. Together, these results establish that gut microbial AzoRs are functionally diverse but sparse in both health and disease, factors that may contribute to non-optimal processing of azo-linked prodrugs and idiopathic IBD drug responses.

Control of ribosomal RNA synthesis by hematopoietic transcription factors

Ribosomal RNAs (rRNAs) are the most abundant cellular RNAs, and their synthesis from rDNA repeats by RNA polymerase I accounts for the bulk of all transcription. Despite substantial variation in rRNA transcription rates across cell types, little is known about cell-type-specific factors that bind rDNA and regulate rRNA transcription to meet tissue-specific needs. Using hematopoiesis as a model system, we mapped about 2,200 ChIP-seq datasets for 250 transcription factors (TFs) and chromatin proteins to human and mouse rDNA and identified robust binding of multiple TF families to canonical TF motifs on rDNA. Using a 47S-FISH-Flow assay developed for nascent rRNA quantification, we demonstrated that targeted degradation of C/EBP alpha (CEBPA), a critical hematopoietic TF with conserved rDNA binding, caused rapid reduction in rRNA transcription due to reduced RNA Pol I occupancy. Our work identifies numerous potential rRNA regulators and provides a template for dissection of TF roles in rRNA transcription.

HTCA: a database with an in-depth characterization of the single-cell human transcriptome

Single-cell RNA-sequencing (scRNA-seq) is one of the most used single-cell omics in recent decades. The exponential growth of single-cell data has immense potential for large-scale integration and in-depth explorations that are more representative of the study population. Efforts have been made to consolidate published data, yet extensive characterization is still lacking. Many focused on raw-data database constructions while others concentrate mainly on gene expression queries. Hereby, we present HTCA (www.htcatlas.org), an interactive database constructed based on ∼2.3 million high-quality cells from ∼3000 scRNA-seq samples and comprised in-depth phenotype profiles of 19 healthy adult and matching fetal tissues. HTCA provides a one-stop interactive query to gene signatures, transcription factor (TF) activities, TF motifs, receptor-ligand interactions, enriched gene ontology (GO) terms, etc. across cell types in adult and fetal tissues. At the same time, HTCA encompasses single-cell splicing variant profiles of 16 adult and fetal tissues, spatial transcriptomics profiles of 11 adult and fetal tissues, and single-cell ATAC-sequencing (scATAC-seq) profiles of 27 adult and fetal tissues. Besides, HTCA provides online analysis tools to perform major steps in a typical scRNA-seq analysis. Altogether, HTCA allows real-time explorations of multi-omics adult and fetal phenotypic profiles and provides tools for a flexible scRNA-seq analysis.

Effective Identification of Bacterial Genomes From Short and Long Read Sequencing Data

With the development of sequencing technology, microbiological genome sequencing analysis has attracted extensive attention. For inexperienced users without sufficient bioinformatics skills, making sense of sequencing data for microbial identification, especially for bacterial identification, through reads analysis is still challenging. In order to address the challenge of effectively analyzing genomic information, in this paper, we develop an effective approach and automatic bioinformatics pipeline called PBGI for bacterial genome identification, performing automatedly and customized bioinformatics analysis using short-reads or long-reads sequencing data produced by multiple platforms such as Illumina, PacBio and Oxford Nanopore. An evaluation of the proposed approach on the practical data set is presented, showing that PBGI provides a user-friendly way to perform bacterial identification through short or long reads analysis, and could provide accurate analyzing results. The source code of the PBGI is freely available at https://github.com/lyotvincent/PBGI.

How to Completely Squeeze a Fungus-Advanced Genome Mining Tools for Novel Bioactive Substances

Fungal species have the capability of producing an overwhelming diversity of bioactive substances that can have beneficial but also detrimental effects on human health. These so-called secondary metabolites naturally serve as antimicrobial "weapon systems", signaling molecules or developmental effectors for fungi and hence are produced only under very specific environmental conditions or stages in their life cycle. However, as these complex conditions are difficult or even impossible to mimic in laboratory settings, only a small fraction of the true chemical diversity of fungi is known so far. This also implies that a large space for potentially new pharmaceuticals remains unexplored. We here present an overview on current developments in advanced methods that can be used to explore this chemical space. We focus on genetic and genomic methods, how to detect genes that harbor the blueprints for the production of these compounds (i.e., biosynthetic gene clusters, BGCs), and ways to activate these silent chromosomal regions. We provide an in-depth view of the chromatin-level regulation of BGCs and of the potential to use the CRISPR/Cas technology as an activation tool.

Structure Prediction, Evaluation, and Validation of GPR18 Lipid Receptor Using Free Programs

The GPR18 receptor, often referred to as the N-arachidonylglycine receptor, although assigned (along with GPR55 and GPR119) to the new class A GPCR subfamily-lipid receptors, officially still has the status of a class A GPCR orphan. While its signaling pathways and biological significance have not yet been fully elucidated, increasing evidence points to the therapeutic potential of GPR18 in relation to immune, neurodegenerative, and cancer processes to name a few. Therefore, it is necessary to understand the interactions of potential ligands with the receptor and the influence of particular structural elements on their activity. Thus, given the lack of an experimentally solved structure, the goal of the present study was to obtain a homology model of the GPR18 receptor in the inactive state, meeting all requirements in terms of protein structure quality and recognition of active ligands. To increase the reliability and precision of the predictions, different contemporary protein structure prediction methods and software were used and compared herein. To test the usability of the resulting models, we optimized and compared the selected structures followed by the assessment of the ability to recognize known, active ligands. The stability of the predicted poses was then evaluated by means of molecular dynamics simulations. On the other hand, most of the best-ranking contemporary CADD software/platforms for its full usability require rather expensive licenses. To overcome this down-to-earth obstacle, the overarching goal of these studies was to test whether it is possible to perform the thorough CADD experiments with high scientific confidence while using only license-free/academic software and online platforms. The obtained results indicate that a wide range of freely available software and/or academic licenses allow us to carry out meaningful molecular modelling/docking studies.

Potential of tellurite resistance in heterotrophic bacteria from mining environments

Untreated mining wastes and improper disposal of high-tech devices generate an environmental increase of bioavailable metalloids, exerting stress on autochthonous microbial populations. Tellurium is a metalloid, an element with raising economic importance; nevertheless, its interaction with living organisms is not yet fully understood. Here we characterized aerobic heterotrophic bacteria, isolated from high metal-content mining residues, able to resist/reduce tellurite into tellurium structures and to determine the presence of confirmed tellurite resistance genetic determinants in resistant strains. We identified over 50 tellurite-resistant strains, among 144 isolates, eight strains reduced tellurite to tellurium at different rates, with the concomitant production of tellurium deposits. Most tellurite resistance genes were found in strains from Bacillales, with the prevalence of genes of the ter operon. This work demonstrated that bacterial isolates, from environments with a persistent selective pressure, are potential candidates for uncovering strategies for tellurite resistance and/or production of valuable Te-containing materials.

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Sites with continuous high metal pressure as a source of Te-resistant bacteria diversity

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Organism-specific Te (IV) reduction produces unique Te (0) insoluble structures

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Unveiled Te resistance genetic determinants and arrangements in Bacillales

The phylogenetic position of zebrafish (Danio rerio) from south african pet shops

BACKGROUND

Zebrafish (Danio rerio), a small freshwater fish that originates from India, Bangladesh, Nepal, Bhutan and northern Myanmar, have been widely used as a model organism for studies of developmental biology and genetics. The current study aimed to determine the origin of South African pet shop stock that are currently being used to establish a laboratory population founded from diverse sources available locally.

METHODS AND RESULTS

Zebrafish DNA was extracted from 65 specimens housed at the University of the Free State (UFS) Department of Genetics. For phylogenetic analysis, cytb sequences were generated from all samples. A further 178 sequences were downloaded from the GenBank database, including sequences of an outgroup species (Danio kyathit). Five microsatellite markers were used to further assess the genetic diversity of the UFS zebrafish specimens. A maximum likelihood analysis was performed for the cytb data. Results of the phylogenetic analyses divided the sequences into three major genetic groups, which was congruent with a previous study on laboratory zebrafish provenance. The SA pet shop fish grouped with the lines from the northern and north-eastern regions of India. High levels of microsatellite genetic diversity were observed for the pet shop sourced population, correlating to what has previously been observed in zebrafish.

CONCLUSION

These results can be used to guide the future development of laboratory lines suited to the needs at the UFS.

Deep learning of a bacterial and archaeal universal language of life enables transfer learning and illuminates microbial dark matter

The majority of microbial genomes have yet to be cultured, and most proteins identified in microbial genomes or environmental sequences cannot be functionally annotated. As a result, current computational approaches to describe microbial systems rely on incomplete reference databases that cannot adequately capture the functional diversity of the microbial tree of life, limiting our ability to model high-level features of biological sequences. Here we present LookingGlass, a deep learning model encoding contextually-aware, functionally and evolutionarily relevant representations of short DNA reads, that distinguishes reads of disparate function, homology, and environmental origin. We demonstrate the ability of LookingGlass to be fine-tuned via transfer learning to perform a range of diverse tasks: to identify novel oxidoreductases, to predict enzyme optimal temperature, and to recognize the reading frames of DNA sequence fragments. LookingGlass enables functionally relevant representations of otherwise unknown and unannotated sequences, shedding light on the microbial dark matter that dominates life on Earth.

Computational methods to analyse microbial systems rely on reference databases which do not capture their full functional diversity. Here the authors develop a deep learning model and apply it using transfer learning, creating biologically useful models for multiple different tasks.

Metagenomics combined with activity-based proteomics point to gut bacterial enzymes that reactivate mycophenolate

Mycophenolate mofetil (MMF) is an important immunosuppressant prodrug prescribed to prevent organ transplant rejection and to treat autoimmune diseases. MMF usage, however, is limited by severe gastrointestinal toxicity that is observed in approximately 45% of MMF recipients. The active form of the drug, mycophenolic acid (MPA), undergoes extensive enterohepatic recirculation by bacterial β-glucuronidase (GUS) enzymes, which reactivate MPA from mycophenolate glucuronide (MPAG) within the gastrointestinal tract. GUS enzymes demonstrate distinct substrate preferences based on their structural features, and gut microbial GUS enzymes that reactivate MPA have not been identified. Here, we compare the fecal microbiomes of transplant recipients receiving MMF to healthy individuals using shotgun metagenomic sequencing. We find that neither microbial composition nor the presence of specific structural classes of GUS genes are sufficient to explain the differences in MPA reactivation measured between fecal samples from the two cohorts. We next employed a GUS-specific activity-based chemical probe and targeted metaproteomics to identify and quantify the GUS proteins present in the human fecal samples. The identification of specific GUS enzymes was improved by using the metagenomics data collected from the fecal samples. We found that the presence of GUS enzymes that bind the flavin mononucleotide (FMN) is significantly correlated with efficient MPA reactivation. Furthermore, structural analysis identified motifs unique to these FMN-binding GUS enzymes that provide molecular support for their ability to process this drug glucuronide. These results indicate that FMN-binding GUS enzymes may be responsible for reactivation of MPA and could be a driving force behind MPA-induced GI toxicity.

Pneumococcal Extracellular Serine Proteases: Molecular Analysis and Impact on Colonization and Disease

The pathobiont Streptococcus pneumoniae causes life-threatening diseases, including pneumonia, sepsis, meningitis, or non-invasive infections such as otitis media. Serine proteases are enzymes that have been emerged during evolution as one of the most abundant and functionally diverse group of proteins in eukaryotic and prokaryotic organisms. S. pneumoniae expresses up to four extracellular serine proteases belonging to the category of trypsin-like or subtilisin-like family proteins: HtrA, SFP, PrtA, and CbpG. These serine proteases have recently received increasing attention because of their immunogenicity and pivotal role in the interaction with host proteins. This review is summarizing and focusing on the molecular and functional analysis of pneumococcal serine proteases, thereby discussing their contribution to pathogenesis.

Diversity and substrate-specificity of green algae and other micro-eukaryotes colonizing amphibian clutches in Germany, revealed by DNA metabarcoding

Amphibian clutches are colonized by diverse but poorly studied communities of micro-organisms. One of the most noted ones is the unicellular green alga, Oophila amblystomatis, but the occurrence and role of other micro-organisms in the capsular chamber surrounding amphibian clutches have remained largely unstudied. Here, we undertook a multi-marker DNA metabarcoding study to characterize the community of algae and other micro-eukaryotes associated with agile frog (Rana dalmatina) clutches. Samplings were performed at three small ponds in Germany, from four substrates: water, sediment, tree leaves from the bottom of the pond, and R. dalmatina clutches. Sampling substrate strongly determined the community compositions of algae and other micro-eukaryotes. Therefore, as expected, the frog clutch-associated communities formed clearly distinct clusters. Clutch-associated communities in our study were structured by a plethora of not only green algae, but also diatoms and other ochrophytes. The most abundant operational taxonomic units (OTUs) in clutch samples were taxa from Chlamydomonas, Oophila, but also from Nitzschia and other ochrophytes. Sequences of Oophila "Clade B" were found exclusively in clutches. Based on additional phylogenetic analyses of 18S rDNA and of a matrix of 18 nuclear genes derived from transcriptomes, we confirmed in our samples the existence of two distinct clades of green algae assigned to Oophila in past studies. We hypothesize that "Clade B" algae correspond to the true Oophila, whereas "Clade A" algae are a series of Chlorococcum species that, along with other green algae, ochrophytes and protists, colonize amphibian clutches opportunistically and are often cultured from clutch samples due to their robust growth performance. The clutch-associated communities were subject to filtering by sampling location, suggesting that the taxa colonizing amphibian clutches can drastically differ depending on environmental conditions.

Molecular diet analysis of neotropical bats based on fecal DNA metabarcoding

Bat communities in the Neotropics are some of the most speciose assemblages of mammals on Earth, with regions supporting more than 100 sympatric species with diverse feeding ecologies. Because bats are small, nocturnal, and volant, it is difficult to directly observe their feeding habits, which has resulted in their classification into broadly defined dietary guilds (e.g., insectivores, carnivores, and frugivores). Apart from these broad guilds, we lack detailed dietary information for many species and therefore have only a limited understanding of interaction networks linking bats and their diet items. In this study, we used DNA metabarcoding of plants, arthropods, and vertebrates to investigate the diets of 25 bat species from the tropical dry forests of Lamanai, Belize. Our results report some of the first detection of diet items for the focal bat taxa, adding rich and novel natural history information to the field of bat ecology. This study represents a comprehensive first effort to apply DNA metabarcoding to bat diets at Lamanai and provides a useful methodological framework for future studies testing hypotheses about coexistence and niche differentiation in the context of modern high-throughput molecular data.

Sedimentary ancient DNA reveals a threat of warming-induced alpine habitat loss to Tibetan Plateau plant diversity

Studies along elevational gradients worldwide usually find the highest plant taxa richness in mid-elevation forest belts. Hence, an increase in upper elevation diversity is expected in the course of warming-related treeline rise. Here, we use a time-series approach to infer past taxa richness from sedimentary ancient DNA from the south-eastern Tibetan Plateau over the last ~18,000 years. We find the highest total plant taxa richness during the cool phase after glacier retreat when the area contained extensive and diverse alpine habitats (14-10 ka); followed by a decline when forests expanded during the warm early- to mid-Holocene (10-3.6 ka). Livestock grazing since 3.6 ka promoted plant taxa richness only weakly. Based on these inferred dependencies, our simulation yields a substantive decrease in plant taxa richness in response to warming-related alpine habitat loss over the next centuries. Accordingly, efforts of Tibetan biodiversity conservation should include conclusions from palaeoecological evidence.

Vegetation Reconstruction From Siberia and the Tibetan Plateau Using Modern Analogue Technique–Comparing Sedimentary (Ancient) DNA and Pollen Data

To reconstruct past vegetation from pollen or, more recently, lake sedimentary DNA (sedDNA) data is a common goal in palaeoecology. To overcome the bias of a researcher’s subjective assessment and to assign past assemblages to modern vegetation types quantitatively, the modern analogue technique (MAT) is often used for vegetation reconstruction. However, a rigorous comparison of MAT-derived pollen-based and sedDNA-based vegetation reconstruction is lacking. Here, we assess the dissimilarity between modern taxa assemblages from lake surface-sediments and fossil taxa assemblages from four lake sediment cores from the south-eastern Tibetan Plateau and northern Siberia using receiver operating characteristic (ROC) curves, ordination methods, and Procrustes analyses. Modern sedDNA samples from 190 lakes and pollen samples from 136 lakes were collected from a variety of vegetation types. Our results show that more modern analogues are found with sedDNA than pollen when applying similarly derived thresholds. In particular, there are few modern pollen analogues for open vegetation such as alpine or arctic tundra, limiting the ability of treeline shifts to be clearly reconstructed. In contrast, the shifts in the main vegetation communities are well captured by sedimentary ancient DNA (sedaDNA). For example, pronounced shifts from late-glacial alpine meadow/steppe to early–mid-Holocene coniferous forests to late Holocene Tibetan shrubland vegetation types are reconstructed for Lake Naleng on the south-eastern Tibetan Plateau. Procrustes and PROTEST analyses reveal that intertaxa relationships inferred from modern sedaDNA datasets align with past relationships generally, while intertaxa relationships derived from modern pollen spectra are mostly significantly different from fossil pollen relationships. Overall, we conclude that a quantitative sedaDNA-based vegetation reconstruction using MAT is more reliable than a pollen-based reconstruction, probably because of the more straightforward taphonomy that can relate sedDNA assemblages to the vegetation surrounding the lake.

A Bittersweet Computational Journey among Glycosaminoglycans

Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the “bitter” and “sweet” aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.

Vegetation Changes in Southeastern Siberia During the Late Pleistocene and the Holocene

Relationships between climate, species composition, and species richness are of particular importance for understanding how boreal ecosystems will respond to ongoing climate change. This study aims to reconstruct changes in terrestrial vegetation composition and taxa richness during the glacial Late Pleistocene and the interglacial Holocene in the sparsely studied southeastern Yakutia (Siberia) by using pollen and sedimentary ancient DNA (sedaDNA) records. Pollen and sedaDNA metabarcoding data using the trnL g and h markers were obtained from a sediment core from Lake Bolshoe Toko. Both proxies were used to reconstruct the vegetation composition, while metabarcoding data were also used to investigate changes in plant taxa richness. The combination of pollen and sedaDNA approaches allows a robust estimation of regional and local past terrestrial vegetation composition around Bolshoe Toko during the last ∼35,000 years. Both proxies suggest that during the Late Pleistocene, southeastern Siberia was covered by open steppe-tundra dominated by graminoids and forbs with patches of shrubs, confirming that steppe-tundra extended far south in Siberia. Both proxies show disturbance at the transition between the Late Pleistocene and the Holocene suggesting a period with scarce vegetation, changes in the hydrochemical conditions in the lake, and in sedimentation rates. Both proxies document drastic changes in vegetation composition in the early Holocene with an increased number of trees and shrubs and the appearance of new tree taxa in the lake’s vicinity. The sedaDNA method suggests that the Late Pleistocene steppe-tundra vegetation supported a higher number of terrestrial plant taxa than the forested Holocene. This could be explained, for example, by the “keystone herbivore” hypothesis, which suggests that Late Pleistocene megaherbivores were able to maintain a high plant diversity. This is discussed in the light of the data with the broadly accepted species-area hypothesis as steppe-tundra covered such an extensive area during the Late Pleistocene.

Bacterial avidins are a widely distributed protein family in Actinobacteria, Proteobacteria and Bacteroidetes

BACKGROUND

Avidins are biotin-binding proteins commonly found in the vertebrate eggs. In addition to streptavidin from Streptomyces avidinii, a growing number of avidins have been characterized from divergent bacterial species. However, a systematic research concerning their taxonomy and ecological role has never been done. We performed a search for avidin encoding genes among bacteria using available databases and classified potential avidins according to taxonomy and the ecological niches utilized by host bacteria.

RESULTS

Numerous avidin-encoding genes were found in the phyla Actinobacteria and Proteobacteria. The diversity of protein sequences was high and several new variants of genes encoding biotin-binding avidins were found. The living strategies of bacteria hosting avidin encoding genes fall mainly into two categories. Human and animal pathogens were overrepresented among the found bacteria carrying avidin genes. The other widespread category were bacteria that either fix nitrogen or live in root nodules/rhizospheres of plants hosting nitrogen-fixing bacteria.

CONCLUSIONS

Bacterial avidins are a taxonomically and ecologically diverse group mainly found in Actinobacteria, Proteobacteria and Bacteroidetes, associated often with plant invasiveness. Avidin encoding genes in plasmids hint that avidins may be horizontally transferred. The current survey may be used as a basis in attempts to understand the ecological significance of biotin-binding capacity.

Challenges of automation and scale: Bioinformatics and the evaluation of proteins to support genetically modified product safety assessments

Bioinformatic analyses of protein sequences play an important role in the discovery and subsequent safety assessment of insect control proteins in Genetically Modified (GM) crops. Due to the rapid adoption of high-throughput sequencing methods over the last decade, the number of protein sequences in GenBank and other public databases has increased dramatically. Many of these protein sequences are the product of whole genome sequencing efforts, coupled with automated protein sequence prediction and annotation pipelines. Published genome sequencing studies provide a rich and expanding foundation of new source organisms and proteins for insect control or other desirable traits in GM products. However, data generated by automated pipelines can also confound regulatory safety assessments that employ bioinformatics. Largely this issue does not arise due to underlying sequence, but rather its annotation or associated metadata, and the downstream integration of that data into existing repositories. Observations made during bioinformatic safety assessments are described.

The Biological Significance of Targeting Acetylation-Mediated Gene Regulation for Designing New Mechanistic Tools and Potential Therapeutics

The molecular interplay between nucleosomal packaging and the chromatin landscape regulates the transcriptional programming and biological outcomes of downstream genes. An array of epigenetic modifications plays a pivotal role in shaping the chromatin architecture, which controls DNA access to the transcriptional machinery. Acetylation of the amino acid lysine is a widespread epigenetic modification that serves as a marker for gene activation, which intertwines the maintenance of cellular homeostasis and the regulation of signaling during stress. The biochemical horizon of acetylation ranges from orchestrating the stability and cellular localization of proteins that engage in the cell cycle to DNA repair and metabolism. Furthermore, lysine acetyltransferases (KATs) modulate the functions of transcription factors that govern cellular response to microbial infections, genotoxic stress, and inflammation. Due to their central role in many biological processes, mutations in KATs cause developmental and intellectual challenges and metabolic disorders. Despite the availability of tools for detecting acetylation, the mechanistic knowledge of acetylation-mediated cellular processes remains limited. This review aims to integrate molecular and structural bases of KAT functions, which would help design highly selective tools for understanding the biology of KATs toward developing new disease treatments.

Considerations for mosquito microbiome research from the Mosquito Microbiome Consortium

In the past decade, there has been increasing interest in mosquito microbiome research, leading to large amounts of data on different mosquito species, with various underlying physiological characteristics, and from diverse geographical locations. However, guidelines and standardized methods for conducting mosquito microbiome research are lacking. To streamline methods in mosquito microbiome research and optimize data quality, reproducibility, and comparability, as well as facilitate data curation in a centralized location, we are establishing the Mosquito Microbiome Consortium, a collaborative initiative for the advancement of mosquito microbiome research. Our overall goal is to collectively work on unraveling the role of the mosquito microbiome in mosquito biology, while critically evaluating its potential for mosquito-borne disease control. This perspective serves to introduce the consortium and invite broader participation. It highlights the issues we view as most pressing to the community and proposes guidelines for conducting mosquito microbiome research. We focus on four broad areas in this piece: (1) sampling/experimental design for field, semi-field, or laboratory studies; (2) metadata collection; (3) sample processing, sequencing, and use of appropriate controls; and (4) data handling and analysis. We finally summarize current challenges and highlight future directions in mosquito microbiome research. We hope that this piece will spark discussions around this area of disease vector biology, as well as encourage careful considerations in the design and implementation of mosquito microbiome research. Video Abstract.

LncRBase V.2: an updated resource for multispecies lncRNAs and ClinicLSNP hosting genetic variants in lncRNAs for cancer patients

The recent discovery of long non-coding RNA as a regulatory molecule in the cellular system has altered the concept of the functional aptitude of the genome. Since our publication of the first version of LncRBase in 2014, there has been an enormous increase in the number of annotated lncRNAs of multiple species other than Human and Mouse. LncRBase V.2 hosts information of 549,648 lncRNAs corresponding to six additional species besides Human and Mouse, viz. Rat, Fruitfly, Zebrafish, Chicken, Cow and C.elegans. It provides additional distinct features such as (i) Transcription Factor Binding Site (TFBS) in the lncRNA promoter region, (ii) sub-cellular localization pattern of lncRNAs (iii) lnc-pri-miRNAs (iv) Possible small open reading frames (sORFs) within lncRNA. (v) Manually curated information of interacting target molecules and disease association of lncRNA genes (vi) Distribution of lncRNAs across multiple tissues of all species. Moreover, we have hosted ClinicLSNP within LncRBase V.2. ClinicLSNP has a comprehensive catalogue of lncRNA variants present within breast, ovarian, and cervical cancer inferred from 561 RNA-Seq data corresponding to these cancers. Further, we have checked whether these lncRNA variants overlap with (i)Repeat elements,(ii)CGI, (iii)TFBS within lncRNA loci (iv)SNP localization in trait-associated Linkage Disequilibrium(LD) region, (v)predicted the potentially pathogenic variants and (vi)effect of SNP on lncRNA secondary structure. Overall, LncRBaseV.2 is a user-friendly database to survey, search and retrieve information about multi-species lncRNAs. Further, ClinicLSNP will serve as a useful resource for cancer specific lncRNA variants and their related information. The database is freely accessible and available at http://dibresources.jcbose.ac.in/zhumur/lncrbase2/.

Discover novel disease-associated genes based on regulatory networks of long-range chromatin interactions

Identifying genes and non-coding genetic variants that are genetically associated with complex diseases and the underlying mechanisms is one of the most important questions in functional genomics. Due to the limited statistical power and the lack of mechanistic modeling, traditional genome-wide association studies (GWAS) is restricted to fully address this question. Based on multi-omics data integration, cell-type specific regulatory networks can be built to improve GWAS analysis. In this study, we developed a new computational infrastructure, APRIL, to incorporate 3D chromatin interactions into regulatory network construction, which can extend the networks to include long-range cis-regulatory links between non-coding GWAS SNPs and target genes. Combinatorial transcription factors that co-regulate groups of genes are also inferred to further expand the networks with trans-regulation. A suite of machine learning predictions and statistical tests are incorporated in APRIL to predict novel disease-associated genes based on the expanded regulatory networks. Important features of non-coding regulatory elements and genetic variants are prioritized in network-based predictions, providing systems-level insights on the mechanisms of transcriptional dysregulation associated with complex diseases.